Fourier Analysis

Produces the Fourier analysis of a data set by computing the Discrete Fourier Transform (DFT) of an input array of complex numbers using a couple of Fast Fourier Transform (FFT) algorithms.

To access this command...

Choose Data - Statistics - Fourier Analysis

For more information on Fourier analysis, refer to the corresponding Wikipedia article.

Data

Input Range: The reference of the range of the data to analyse.

Results to: The reference of the top left cell of the range where the results will be displayed.

Input range has label: Mark when the first row or column of the input array is actually a label and not part of the data analysis.

Input Range is a 2 x N or N x 2 range representing an array of complex number to be transformed, where N is the length of the array. The array represents the real and imaginary parts of the data.

Grouped By

Select whether the input data has columns or rows layout.

Options:

Inverse: When checked, calculates the inverse Discrete Fourier Transform.

Polar: When checked, the results are in polar coordinates (magnitude, phase).

Minimum magnitude for polar form output (in dB): used only when output is in polar form. All frequency components with magnitude less than this value in decibels will be suppressed with a zero magnitude-phase entry. This is very useful when looking at the magnitude-phase spectrum of a signal because there is always some very tiny amount of rounding error when doing FFT algorithms and results in incorrect non-zero phase for non-existent frequencies. By providing a suitable value to this parameter, these non-existent frequency components can be suppressed.

Open file with example:

Examples

The source data for this example is the same of the FOURIER function page.

Related Topics

• Sampling
• Descriptive Statistics
• Analysis of Variance (ANOVA)
• Correlation
• Covariance
• Exponential Smoothing
• Moving Average
• Regression Analysis
• Paired t-test
• F-test
• Z-test
• Chi-square test
• Fourier Analysis